{
  "id": 117,
  "url": "https://arxiv.org/abs/2607.07669v1",
  "title": "DiaLLM: An Investigation into the Robustness-Generation Gap in English Dialect Adaptation",
  "summary": "Large language models increasingly \\emph{understand} dialectal English, yet still \\emph{produce} only standard, US-leaning English, leaving dialectal generation, the harder half of the problem, largely unaddressed. We introduce \\textbf{DiaLLM}, which continually pretrains three open-weight language model families on the International Corpus of English and applies implicit and explicit post-training paradigms, each combined with three model alignment strategies, giving the first controlled compar",
  "authors": "Jordan Painter, Dipankar Srirag, Adarsh Kappiyath, Diptesh Kanojia, Aditya Joshi, Lu Yin",
  "category": "research",
  "topics": "safety-alignment,finance-investment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-08T17:24:27.000Z",
  "fetched_at": "2026-07-14T14:14:19.967Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/117",
  "original_url": "https://arxiv.org/abs/2607.07669v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}